Dynamic adversarial joint domain adaptation for unsupervised cross-machine bearing fault diagnosis
Structural Health Monitoring: An International Journal
Published online on January 07, 2026
Abstract
Structural Health Monitoring, Ahead of Print.
Unsupervised domain adaptation (UDA) methodologies have demonstrated notable success in solving the distribution shifts between training and testing data for rotating machinery fault diagnosis. However, their effectiveness remains limited in cross-machine ...
Unsupervised domain adaptation (UDA) methodologies have demonstrated notable success in solving the distribution shifts between training and testing data for rotating machinery fault diagnosis. However, their effectiveness remains limited in cross-machine ...